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Improving the efficiency of nondeterministic independent and-parallel systems
Affiliation:1. Laboratory for Logic and Databases, Dept of Computer Science, New Mexico State University. Las Cruces, NM, U.S.A.;2. Facultad de Informática, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain;1. Wangxuan Institute of Computer Technology, Peking University, Beijing, China;2. The MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China;3. Open University of China, Beijing, China;1. University of Science and Technology of China, Hefei, Anhui, 230027, China;2. National University of Singapore, 119077, Singapore;3. University of Hong Kong, China;1. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China;2. State Key Laboratory of Mathematical Engineering and Advanced Computing, Wuxi, China
Abstract:We present the design and implementation of the and-parallel component of ACE. ACE is a computational model for the full Prolog language that simultaneously exploits both or-parallelism and independent and-parallelism. A high-performance implementation of the ACE model has been realized and its performance reported in this paper. We discuss how some of the standard problems which appear when implementing and-parallel systems are solved in ACE. We then propose a number of optimizations aimed at reducing the overheads and the increased memory consumption which occur in such systems when using previously proposed solutions. Finally, we present results from an implementation of ACE which includes the optimizations proposed. The results show that ACE exploits and-parallelism with high efficiency and high speedups. Furthermore, they also show that the proposed optimizations, which are applicable to many other and-parallel systems, significantly decrease memory consumption and increase speedups and absolute performance both in forward execution and during backtracking.
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